



'''simple docstring'''



import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / 'utils'))

from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


lowerCAmelCase_  :							Optional[Any]             =    get_tests_dir('fixtures')
class 						lowerCamelCase_				(       unittest.TestCase      ):







						def        __lowercase     (	self :   int					):

													"""simple docstring"""
													# A mock response for an HTTP head request to emulate server down
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      mock.Mock()
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      5_00
													SCREAMING_SNAKE_CASE       :   Dict         =      {}
													SCREAMING_SNAKE_CASE       :   int         =      HTTPError
													SCREAMING_SNAKE_CASE       :   Dict         =      {}

													# Download this model to make sure it's in the cache.
													SCREAMING_SNAKE_CASE       :   List[Any]         =      WavaVecaFeatureExtractor.from_pretrained('''hf-internal-testing/tiny-random-wav2vec2'''					)
													# Under the mock environment we get a 500 error when trying to reach the model.
													with mock.patch('''requests.Session.request'''					,     return_value=lowerCAmelCase__					) as mock_head:
																				SCREAMING_SNAKE_CASE       :   str         =      WavaVecaFeatureExtractor.from_pretrained('''hf-internal-testing/tiny-random-wav2vec2'''					)
																				# This check we did call the fake head request
																				mock_head.assert_called()







						def        __lowercase     (	self :   Dict					):

													"""simple docstring"""
													# This test is for deprecated behavior and can be removed in v5
													SCREAMING_SNAKE_CASE       :   int         =      WavaVecaFeatureExtractor.from_pretrained(
													    '''https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json'''					)


@is_staging_test
class 						lowerCamelCase_				(       unittest.TestCase      ):







						@classmethod
						def        __lowercase     (	cls :   List[Any]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      TOKEN
													HfFolder.save_token(lowerCAmelCase__					)







						@classmethod
						def        __lowercase     (	cls :   str					):

													"""simple docstring"""
													try:
																				delete_repo(token=cls._token					,     repo_id='''test-feature-extractor'''					)
													except HTTPError:
																				pass

													try:
																				delete_repo(token=cls._token					,     repo_id='''valid_org/test-feature-extractor-org'''					)
													except HTTPError:
																				pass

													try:
																				delete_repo(token=cls._token					,     repo_id='''test-dynamic-feature-extractor'''					)
													except HTTPError:
																				pass







						def        __lowercase     (	self :   List[str]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   str         =      WavaVecaFeatureExtractor.from_pretrained(lowerCAmelCase__					)
													feature_extractor.push_to_hub('''test-feature-extractor'''					,     use_auth_token=self._token					)

													SCREAMING_SNAKE_CASE       :   Any         =      WavaVecaFeatureExtractor.from_pretrained(F"""{USER}/test-feature-extractor"""					)
													for k, v in feature_extractor.__dict__.items():
																				self.assertEqual(lowerCAmelCase__					,     getattr(lowerCAmelCase__					,     lowerCAmelCase__					)					)

													# Reset repo
													delete_repo(token=self._token					,     repo_id='''test-feature-extractor'''					)

													# Push to hub via save_pretrained
													with tempfile.TemporaryDirectory() as tmp_dir:
																				feature_extractor.save_pretrained(
																				    lowerCAmelCase__					,     repo_id='''test-feature-extractor'''					,     push_to_hub=lowerCAmelCase__					,     use_auth_token=self._token					)

													SCREAMING_SNAKE_CASE       :   Any         =      WavaVecaFeatureExtractor.from_pretrained(F"""{USER}/test-feature-extractor"""					)
													for k, v in feature_extractor.__dict__.items():
																				self.assertEqual(lowerCAmelCase__					,     getattr(lowerCAmelCase__					,     lowerCAmelCase__					)					)







						def        __lowercase     (	self :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      WavaVecaFeatureExtractor.from_pretrained(lowerCAmelCase__					)
													feature_extractor.push_to_hub('''valid_org/test-feature-extractor'''					,     use_auth_token=self._token					)

													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      WavaVecaFeatureExtractor.from_pretrained('''valid_org/test-feature-extractor'''					)
													for k, v in feature_extractor.__dict__.items():
																				self.assertEqual(lowerCAmelCase__					,     getattr(lowerCAmelCase__					,     lowerCAmelCase__					)					)

													# Reset repo
													delete_repo(token=self._token					,     repo_id='''valid_org/test-feature-extractor'''					)

													# Push to hub via save_pretrained
													with tempfile.TemporaryDirectory() as tmp_dir:
																				feature_extractor.save_pretrained(
																				    lowerCAmelCase__					,     repo_id='''valid_org/test-feature-extractor-org'''					,     push_to_hub=lowerCAmelCase__					,     use_auth_token=self._token					)

													SCREAMING_SNAKE_CASE       :   List[Any]         =      WavaVecaFeatureExtractor.from_pretrained('''valid_org/test-feature-extractor-org'''					)
													for k, v in feature_extractor.__dict__.items():
																				self.assertEqual(lowerCAmelCase__					,     getattr(lowerCAmelCase__					,     lowerCAmelCase__					)					)







						def        __lowercase     (	self :   Tuple					):

													"""simple docstring"""
													CustomFeatureExtractor.register_for_auto_class()
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      CustomFeatureExtractor.from_pretrained(lowerCAmelCase__					)

													feature_extractor.push_to_hub('''test-dynamic-feature-extractor'''					,     use_auth_token=self._token					)

													# This has added the proper auto_map field to the config
													self.assertDictEqual(
													    feature_extractor.auto_map					,     {'''AutoFeatureExtractor''': '''custom_feature_extraction.CustomFeatureExtractor'''}					,     )

													SCREAMING_SNAKE_CASE       :   List[Any]         =      AutoFeatureExtractor.from_pretrained(
													    F"""{USER}/test-dynamic-feature-extractor"""					,     trust_remote_code=lowerCAmelCase__					)
													# Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
													self.assertEqual(new_feature_extractor.__class__.__name__					,     '''CustomFeatureExtractor'''					)









'''simple docstring'''



import os

lowerCAmelCase_  :							Union[str, Any]             =    {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
def        UpperCAmelCase (    A	:					str					):
							SCREAMING_SNAKE_CASE       :   str         =      0

							SCREAMING_SNAKE_CASE       :   List[str]         =      0
							while index < len(A					) - 1:
														SCREAMING_SNAKE_CASE       :   Dict         =      SYMBOLS[numerals[index]]
														SCREAMING_SNAKE_CASE       :   str         =      SYMBOLS[numerals[index + 1]]
														if current_value < next_value:
																					total_value -= current_value
														else:
																					total_value += current_value
														index += 1
							total_value += SYMBOLS[numerals[index]]

							return total_value
def        UpperCAmelCase (    A	:					int					):
							SCREAMING_SNAKE_CASE       :   Any         =      ''''''

							SCREAMING_SNAKE_CASE       :   Dict         =      num // 1000
							numerals += m_count * "M"
							num %= 1000

							SCREAMING_SNAKE_CASE       :   str         =      num // 100
							if c_count == 9:
														numerals += "CM"
														c_count -= 9
							elif c_count == 4:
														numerals += "CD"
														c_count -= 4
							if c_count >= 5:
														numerals += "D"
														c_count -= 5
							numerals += c_count * "C"
							num %= 100

							SCREAMING_SNAKE_CASE       :   Any         =      num // 10
							if x_count == 9:
														numerals += "XC"
														x_count -= 9
							elif x_count == 4:
														numerals += "XL"
														x_count -= 4
							if x_count >= 5:
														numerals += "L"
														x_count -= 5
							numerals += x_count * "X"
							num %= 10

							if num == 9:
														numerals += "IX"
														num -= 9
							elif num == 4:
														numerals += "IV"
														num -= 4
							if num >= 5:
														numerals += "V"
														num -= 5
							numerals += num * "I"

							return numerals
def        UpperCAmelCase (    A	:					str = "/p089_roman.txt"					):
							SCREAMING_SNAKE_CASE       :   List[str]         =      0

							with open(os.path.dirname(A					) + roman_numerals_filename					) as filea:
														SCREAMING_SNAKE_CASE       :   str         =      filea.readlines()

							for line in lines:
														SCREAMING_SNAKE_CASE       :   Any         =      line.strip()
														SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      parse_roman_numerals(A					)
														SCREAMING_SNAKE_CASE       :   Any         =      generate_roman_numerals(A					)
														savings += len(A					) - len(A					)

							return savings


if __name__ == "__main__":
							print(f'{solution() = }')




